Table 9:

Correlation model between the SNPs for the first-order Markov chain computed by using (3). The first column shows the different states of sequential SNPs and the remaining columns show the probabilities. In this example, we do not consider the SNPs before x₁, and hence in the correlation model, all states of x₁ are equally likely.

	P(x1)	$\text{P}\left(x_2\mid x_1\right)$	$\text{P}\left(x_3\mid x_2\right)$
xj = 0, xj−1 = 0	0.33	0.50	0.75
xj = 0, xj−1 = 1	0.33	1.00	0.00
xj = 0, xj−1 = 2	0.33	0.50	0.00
xj = 1, xj−1 = 0	0.33	0.50	0.25
xj = 1, xj−1 = 1	0.33	0.00	0.50
xj = 1, xj−1 = 2	0.33	0.50	0.00
xj = 2, xj−1 = 0	0.33	0.00	0.00
xj = 2, xj−1 = 1	0.33	0.00	0.50
xj = 2, xj−1 = 2	0.33	0.00	0.00